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At least 37 records · Page 2

Monitoring for Flight Path Management: Inputs to Pilot Monitoring Training

The commercial aviation industry world-wide has identified a need for improved pilot monitoring (e.g., ICAO, 2016). More specifically, aviation safety data indicate that failures in pilots' monitoring for flight path management (FPM) have contributed to a range of undesired outcomes: accidents, major upsets, and non-compliance with ATC guidance. The FAA has further stated that these types of FPM failures are likely to worsen with the increasingly complex air traffic control systems and FPM concepts proposed for NextGen (https://www.faa.gov/nextgen/what_is_nextgen/) operations (e.g., see Hah et al., 2017). An important element of this additional complexity will be the introduction of new automation or artificial intelligence that is intended to work with the flight crew but can add additional monitoring burdens. One potential mitigation for this situation is to enhance pilot training for effective monitoring. NASA Ames Research Center was asked to identify and evaluate training approaches that have the potential to enhance pilots' ability to effectively monitor for FPM (with the result of improved awareness). The focus of this work is to identify, develop or validate training guidance to improve pilot monitoring/awareness regarding FPM and mitigate the recent trend of accidents and incidents, especially Loss of Control (LOC) events. The result of this work should be guidance for FAA training and standards organizations—such as the Air Carrier Training Aviation Rulemaking Committee (ACT ARC)—to aid in reducing the risk of incidents and accidents due to inadequate pilot monitoring/awareness.

Feary, Mike↗

Towards 5G-Enabled Operational Technology for Process Monitoring and Network Slicing

Cyber-Physical Systems (CPS) are deployed to monitor physical processes in critical cyber-enabled services like power generation. However, CPS ecosystems are typically designed without robust security. While it is important to ensure optimal performance of the Operational Technology (OT) environments, security cannot be overlooked. To modernize traditional OT services, 5G technology is being integrated. 5G technology offers low latency and high availability, making it a suitable infrastructure for managing and monitoring physical processes. How-ever, integrating 5G mechanisms into large-scale OT networks introduces new implementation and performance challenges. Therefore, this paper presents a 5G-enabled CPS architecture (5G-CPS) that describes the necessary components, services, and communication protocols and conducts feasibility study to integrate 5G technology in industrial control system networks to understand the performance merits. The 5G-CPS architecture aims to minimize implementation and operational challenges associated with integrating 5G technology into constrained OT.

Aguayo, Jared M.↗

Integrating 5G Technology for Improved Process Monitoring and Network Slicing in ICS

Industrial Control Systems (ICS) are crucial for monitoring physical processes that support essential cyber-enabled services like power generation. The use of proprietary communication and lack of effective intrusion detection mechanisms pose constraints for efficient operation. Therefore, there is a need to modernize these systems with decentralized technologies like Edge Computing and 5G. However, integrating 5G and Edge Computing into large-scale ICS networks presents implementation and performance challenges. To address these challenges, this paper proposes an integrated ICS architecture that combines 5G and Edge Computing technologies with traditional ICS protocols. The objective is to minimize implementation and operational difficulties while improving the monitoring of physical processes and enabling robust intrusion detection. The proposed architecture outlines the necessary components, services, and communication protocols required for the integration of 5G and Edge Computing.

Aguayo, Jared M.↗

Long-term ultrasonic monitoring of concrete affected by alkali-silica reaction

This article presents continuous monitoring results of alkali-silica reaction (ASR) development in concrete specimens for over 400 days using ultrasonic testing and expansion measurements. Eight concrete specimens with nonreactive aggregate (Control), reactive coarse aggregate, and reactive fine aggregates were cast with two reinforced confinement conditions. The specimens were conditioned in an environmental chamber with high temperature and humidity (38°C and 90% relative humidity) to accelerate the ASR development. A multichannel ultrasonic monitoring system was developed to collect ultrasonic signals automatically, and the expansions in three directions were measured periodically. Results showed that the relative velocity change could detect the ASR initiation in all reactive specimens and show a correlation with expansion in the early stage. However, these correlations are inconsistent for different ASR specimens, and the velocity change becomes less sensitive to ASR damage in the late stage (after 300 days). Irrecoverable velocity drop was observed during every chamber shutdown period, especially in specimens with higher levels of ASR damage. This phenomenon suggests that the nonlinear ultrasonic response caused by the ambient temperature variation may indicate the ASR damage.

Engineering↗

Geophysical Characterization and Monitoring of the 200 Area Treated Effluent Disposal Facility to Support Permit Renewal; TEDF Geophysical Monitoring

The Treated Effluent Disposal Facility (TEDF), located in the 200 East Area of the Hanford Site, is a site where non-hazardous and non-radioactive liquid wastes are disposed into two state-permitted infiltration basins. In 2016, the Washington State Department of Ecology denied a permit renewal request for TEDF due to the inability to adequately assess the impact of TEDF discharge water on the underlying groundwater quality. TEDF overlies the relatively impermeable Ringold Lower Mud (RLM) unit, whose upper contact lies in the vadose zone approximately 30 m below ground surface and approximately 10 m above the water table boundary. The RLM is assumed to isolate TEDF discharge water from the natural groundwater aquifer, which is monitored using wellbores screened below the RLM. Therefore, samples collected from monitoring wells near TEDF are not considered representative of TEDF discharge water. Rather, TEDF discharge water is assumed to mound on top of the RLM to form a perched aquifer. To support permitting of the TEDF, a new monitoring well is required that can be used to sample water from the presumed perched water aquifer above the RLM. Ideally, the screened section of the well would be located at the peak of the perched water mound(s), which presumably occurs at the point of maximum vertical flux from TEDF to the RLM, or equivalently where the dominant infiltration flow paths reach the RLM. This report describes how time-lapse 3D electrical resistivity tomography (ERT) was used in conjunction with nominal TEDF discharge operations to image the dominant flow paths from each pond to the RLM. Results are summarized in Figure ES.1. Figure ES.1A shows a satellite image of the TEDF overlain by an array of surface ERT electrodes. The solid and dashed black circles denote the zones of maximum vertical flux at the RLM within the south and north ponds, respectively, and presumably the regions where perched water peaks during discharge. Figure ES.1B shows time-lapse difference imaging results approximately 15 days after switching discharge from the south pond to the north pond. Blue iso-surfaces beneath the north pond denote regions of increasing bulk electrical conductivity caused by increasing saturation due to infiltrating water. Red iso-surfaces beneath the south pond denote regions that were previously saturated during the south pond discharge and are now de-saturating, causing a decrease in bulk electrical conductivity. In both cases, the zones of maximum change mark the dominant flow paths to the RLM. Figure ES.1C shows time-lapse imaging results approximately 15 days after switching discharge from the north pond to the south pond. In this case, blue iso-surfaces mark the dominant flow paths to the RLM from the south pond. The red iso-surfaces mark the dominant flow paths that existed during discharge to the north pond. The regions of maximum change in bulk conductivity (due to saturation or desaturation) that mark the primary flow paths are equivalent in both cases and denoted by the dashed solid and black circles. If a perched water zone forms on the RLM, it is likely to mound within or near the dashed circle during discharge to the north pond, and in the solid circle during discharge to the south pond. In other words, if perched water mounding occurs, the circles mark the optimum locations suggested by the ERT imaging for monitoring boreholes to be placed, enabling samples to be collected that are representative of TEDF discharge impacts on groundwater quality.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

In-Process Monitoring and Structural Health Monitoring of Large-Scale Additive Manufacturing Using Acoustic Emission Technique

ORNL collaborated with MISTRAS Group, Inc. to investigate acoustic emission (AE) as a structural health monitoring (SHM) method for large-scale additive manufacturing (AM). Large-scale AM is being adapted as method of producing large structures in a short lead time and cost-effective way. With the growing advancement in AM techniques and application, machine monitoring and part qualification is highly needed. There has been leading research focused on the manufacturing, feedstock material but minimum research on the SHM, defect detection, and nondestructive evaluation (NDE) for AM. Scanning large structure using conventional nondestructive testing (NDT) techniques, such as ultrasound or X-ray, and searching for potential defects can be very time consuming, challenging and cost prohibitive. AE is a passive technique that can be used to monitor and locate defect progression in large structure by distributing group of sensors around the part. This project utilized AE technique and system manufactured/designed by MISTRAS Group to monitor large-scale AM equipment (i.e. Big Area Additive Manufacturing (BAAM) system located at the Oak Ridge National Laboratory – Manufacturing Demonstration Facility (ORNL-MDF) and the printed parts it produces. The AE system provided valuable insight on defect development/progression during and post-printing process.

36 MATERIALS SCIENCE↗

Feasibility Study of a Rotorcraft Health and Usage Monitoring System ( HUMS): Usage and Structural Life Monitoring Evaluation

The objective of this study was to evaluate two techniques, Flight Condition Recognition (FCR) and Flight Load Synthesis (FLS), for usage monitoring and assess the potential benefits of extending the retirement intervals of life-limited components, thus reducing the operator's maintenance and replacement costs. Both techniques involve indirect determination of loads using measured flight parameters and subsequent fatigue analysis to calculate the life expended on the life-limited components. To assess the potential benefit of usage monitoring, the two usage techniques were compared to current methods of component retirement. In addition, comparisons were made with direct load measurements to assess the accuracy of the two techniques. The data that was used for the evaluation of the usage monitoring techniques was collected under an independent HUMS Flight trial program, using a commercially available HUMS and data recording system. The usage data collect from the HUMS trial aircraft was analyzed off-line using PC-based software that included the FCR and FLS techniques. In the future, if the technique prove feasible, usage monitoring would be incorporated into the onboard HUMS.

Dickson, B.↗

Autonomous Performance Monitoring System: Monitoring and Self-Tuning (MAST)

Maintaining the long-term performance of software onboard a spacecraft can be a major factor in the cost of operations. In particular, the task of controlling and maintaining a future mission of distributed spacecraft will undoubtedly pose a great challenge, since the complexity of multiple spacecraft flying in formation grows rapidly as the number of spacecraft in the formation increases. Eventually, new approaches will be required in developing viable control systems that can handle the complexity of the data and that are flexible, reliable and efficient. In this paper we propose a methodology that aims to maintain the accuracy of flight software, while reducing the computational complexity of software tuning tasks. The proposed Monitoring and Self-Tuning (MAST) method consists of two parts: a flight software monitoring algorithm and a tuning algorithm. The dependency on the software being monitored is mostly contained in the monitoring process, while the tuning process is a generic algorithm independent of the detailed knowledge on the software. This architecture will enable MAST to be applicable to different onboard software controlling various dynamics of the spacecraft, such as attitude self-calibration, and formation control. An advantage of MAST over conventional techniques such as filter or batch least square is that the tuning algorithm uses machine learning approach to handle uncertainty in the problem domain, resulting in reducing over all computational complexity. The underlying concept of this technique is a reinforcement learning scheme based on cumulative probability generated by the historical performance of the system. The success of MAST will depend heavily on the reinforcement scheme used in the tuning algorithm, which guarantees the tuning solutions exist.

Peterson, Chariya↗

Design for Vibration Monitoring: A Methodology for Reliable and Cost-Effective Vibration Monitoring

The purpose of health monitoring systems is to detect failures or defects for increased safety and performance and to provide on-condition maintenance with reduced costs. The problems associated with health monitoring systems include high rates of false alarms and missed failures, which make monitoring an unreliable and costly task. The reason for this is that unaccounted variations invalidate signal modeling assumptions. Our approach was to focus on vibration monitoring of rotating components. We analyzed baseline signals to determine statistical variations, identify and model factors that influence vibrations (pre-production vs. post-production variations), determine hit and false alarm rates with baseline flight data, model and predict effects of defects and variations on vibrations, and develop algorithms and metrics for failure and anomaly detection in the presence of variations.

Tumer, Irem Y.↗

Inductive monitoring system constructed from nominal system data and its use in real-time system monitoring

The present invention relates to an Inductive Monitoring System (IMS), its software implementations, hardware embodiments and applications. Training data is received, typically nominal system data acquired from sensors in normally operating systems or from detailed system simulations. The training data is formed into vectors that are used to generate a knowledge database having clusters of nominal operating regions therein. IMS monitors a system's performance or health by comparing cluster parameters in the knowledge database with incoming sensor data from a monitored-system formed into vectors. Nominal performance is concluded when a monitored-system vector is determined to lie within a nominal operating region cluster or lies sufficiently close to a such a cluster as determined by a threshold value and a distance metric. Some embodiments of IMS include cluster indexing and retrieval methods that increase the execution speed of IMS.

Iverson, David L.↗

All-Sky Monitoring with the Fermi Gamma Ray Burst Monitor

We are currently monitoring the transient hard X-ray/soft gamma ray sky using the Gamma Ray Burst Monitor (GBM) on-board Fermi. The twelve GBM NaI detectors span 8 keV to 1MeV, while the two GBM BGO detectors span about 150 keV to 40 MeV. With GBM, we detect transient events on multiple timescales. Brief events, such as Gamma Ray Bursts, Solar flares, and magnetar bursts are detected with on-board triggers. On longer timescales, we use the Earth occultation technique to monitor a number of sources, including X-ray binaries, AGN, and solar flaring activity. To date we have detected 7 sources above 100 keV. Transient activity from accretion-powered pulsars is monitored using epoch-folding techniques. With GBM we track the pulsed flux and frequency for a number of pulsars. We will present highlights of GBM observations on various timescales.

Wilson-Hodge, Colleen A.↗

Earth Occultation Monitoring with the Fermi Gamma Ray Burst Monitor

Using the Gamma Ray Burst Monitor (GBM) on-board Fermi, we are monitoring the hard X-ray/soft gamma ray sky using the Earth occultation technique (EOT). Each time a source in our catalog is occulted by (or exits occultation by) the Earth, we measure its flux using the change in count rates due to the occultation. Currently we are using CTIME data with 8 energy channels spanning 8 keV to 1 MeV for the GBM NaI detectors for daily monitoring. Light curves, updated daily, are available on our website http://heastro.phys.lsu.edu/gbm. Our software is also capable of performing the Earth occultation monitoring using up to 128 energy bands, or any combination of those bands, using our 128-channel, 4-s CSPEC data. The GBM BGO detectors, sensitive from about 200 keV to 40 keV, can also be used with this technique. In our standard application of the EOT, we use a catalog of sources to drive the measurements. To ensure that our catalog is complete, our team has developed an Earth occultation imaging method. In this talk, I will describe both techniques and the current data products available. I will highlight recent and important results from the GBM EOT, including the current status of our observations of hard X-ray variations in the Crab Nebula.

Wilson-Hodge, Colleen A.↗

Monitoring of the Atmosphere on the International Space Station with the Air Quality Monitor

During the early years of human spaceflight, short duration missions allowed for monitoring of the spacecraft environment to be performed via archival sampling, in which samples were returned to Earth for analysis. With the construction of the International Space Station (ISS) and the accompanying extended mission durations, the need for enhanced, real-time monitors became apparent. The Volatile Organic Analyzer (VOA) operated on ISS for 7 years, where it assessed trace volatile organic compounds in the cabin air. The large and fixed-position VOA was eventually replaced with the smaller Air Quality Monitor (AQM). Since March 2013, the atmosphere of the U.S. Operating Segment (USOS) has been monitored in near real-time by a pair of AQMs. These devices consist of a gas chromatograph (GC) coupled with a differential mobility spectrometer (DMS) and currently target detection list of 22 compounds. These targets are of importance to both crew health and the Environmental Control and Life Support Systems (ECLSS) on ISS. Data is collected autonomously every 73 hours, though the units can be controlled remotely from mission control to collect data more frequently during contingency or troubleshooting operations. Due to a nominal three-year lifetime on-orbit, the initial units were replaced in February 2016. This paper will focus on the preparation and use of the AQMs over the past several years. A description of the technical aspects of the AQM will be followed by lessons learned from the deployment and operation of the first set of AQMs. These lessons were used to improve the already-excellent performance of the instruments prior to deployment of the replacement units. Data trending over the past several years of operation on ISS will also be discussed, including data obtained during a survey of the USOS modules. Finally, a description of AQM use for contingency and investigative studies will be presented.

Wallace William T.↗

Radiation portal monitor data file format for comprehensive background radiation monitoring

Radiation portal monitors (RPMs) are widely used at border security checkpoints to detect the presence of radioactive materials in people, vehicles, and cargo. Typically, RPM detection systems consist of two pillars equipped with gamma and neutron detectors. To improve detection efficiency, RPMs employ techniques such as a limited energy window, dynamic alarm thresholds, and lead shielding. However, without continuous monitoring of background radiation, signal interpretation can be compromised, because environmental factors and mechanical failures can cause fluctuations. Here, we introduce a daily file format that logs gamma background and neutron background radiation levels continuously over a 24 h period; this format is different from traditional formats that record data only when the RPM is active or occupied. The approach enables RPM operators and analysts to (1) identify and diagnose malfunctioning components, (2) adjust system settings to account for dynamic environmental factors, and (3) use the recorded data to characterize outer space phenomena. Continuous background reporting is essential for identifying issues such as faulty connections, voltage divider failures, and errors in background updates. Continuous background reporting also enables the detection of external influences, including nearby X-ray scanners, temperature fluctuations, rainfall, cosmic radiation, and lunar phase changes. These data files are designed to be easily evaluated and parsed using common tools, and a quick review by an expert is often sufficient for problem diagnosis. We anticipate that continuous background radiation monitoring and these new strategies will significantly improve the accuracy and reliability of RPM systems, reducing the rate of false alarms and enhancing overall system performance.

Background radiation monitoring↗

Multielectrode Array Sensors to Enable Long-Duration Corrosion Monitoring and Control of Concentrating Solar Power Systems

Molten mixtures of MgCl2-KCl-NaCl are promising heat transfer fluid (HTF) candidates for the next generation of concentrating solar power systems (Gen3 CSP), because of their low cost, high decomposition temperature, and favorable heat transfer characteristics. However, if the chemistry of the salts is not properly controlled, molten chlorides can cause corrosion of high-temperature metal alloys, such as Inconel (R), in CSP systems. Here we demonstrate a corrosion monitoring system that can be used to monitor the health of the structural alloys over long durations. The monitoring system includes a multielectrode array voltammetry sensor that measures the redox potential of molten MgCl2-KCl-NaCl mixture as well as the presence of corrosion products and impurities. The sensors have been successfully operated in static molten salt environments for long durations, and are capable of detecting corrosion products, such as Cr2+ and Fe2+, quantitatively at low concentrations (i.e., approximately 100 ppm) with less than 4% error.

Concentrated solar power↗

Integration of seismic-pressure-petrophysics inversion of continuous active-seismic monitoring data for monitoring and quantifying CO 2 plume (Final Report)

The overall objective of this project is to develop and validate an integrated package of joint seismic-pressure-petrophysics inversion (jSPPI) of continuous active-source seismic monitoring dataset capable of providing real-time monitoring of CO 2 plume during geologic carbon sequestration (GCS). The three specific developments include: (a) the methodologies for fast seismic full waveform inversion of continuous active source seismic monitoring, (CASSM) datasets for simultaneously estimating velocity and attenuation, and with data assimilation; (b) joint Bayesian petrophysical inversion of seismic models and pressure data for providing and updating CO 2 saturation models; (c) the methods using multiple datasets including (Crainfield and Frio-II borehole) synthetic, laboratory, and field CASSM datasets. The outcomes of jSPPI include (a) a workflow for processing CASSM data, (b) Bayesian inversion algorithms using CASSM data and pressure response data, and (c) integration with data assimilation algorithms for continuously updating site-specific models used for prediction and reservoir management. The validation of joint FWI will be conducted using synthetic models based on the Cranfield and Frio experiments as well as field CASSM datasets collected as part of the Frio-II pilot injection. To quantify and map the mass and distribution of CO 2 (saturation), we will jointly invert velocity and attenuation measurements from the FWI with a Bayesian approach using a rock physics model for attenuation (e.g., White’s attenuation model with two selected patch sizes (White, 1976; Dutta and Seriff, 1979)). The Bayesian inversion will be applied to each time step in the CASSM survey in an updating scheme, which integrates with an ensemble of reservoir simulations at each step. A more complete experimental validation dataset will be collected as part of a mesoscale (2-3 m) gas-CO 2 injection experiment utilizing a higher frequency version of the CASSM system developed for laboratory studies; the integrated inversion will be demonstrated using this dataset which will provide both a dense geometry as well as more precise secondary confirmation measurements (e.g. saturation) typically not available in the field. The resulting real-time map of CO 2 saturation is able to provide a deeper scientific understanding of the complex, time-varying dynamics of subsurface fluid flow migration path as well as the rapid detection of CO 2 leakage hazards.

25 ENERGY STORAGE↗

NASA's Carbon Monitoring System Flux-Pilot Project: A Multi-Component Analysis System for Carbon-Cycle Research and Monitoring

The importance of greenhouse gas increases for climate motivates NASA s observing strategy for CO2 from space, including the forthcoming Orbiting Carbon Observatory (OCO-2) mission. Carbon cycle monitoring, including attribution of atmospheric concentrations to regional emissions and uptake, requires a robust modeling and analysis infrastructure to optimally extract information from the observations. NASA's Carbon-Monitoring System Flux-Pilot Project (FPP) is a prototype for such analysis, combining a set of unique tools to facilitate analysis of atmospheric CO2 along with fluxes between the atmosphere and the terrestrial biosphere or ocean. NASA's analysis system is unique, in that it combines information and expertise from the land, oceanic, and atmospheric branches of the carbon cycle and includes some estimates of uncertainty. Numerous existing space-based missions provide information of relevance to the carbon cycle. This study describes the components of the FPP framework, assessing the realism of computed fluxes, thus providing the basis for research and monitoring applications. Fluxes are computed using data-constrained terrestrial biosphere models and physical ocean models, driven by atmospheric observations and assimilating ocean-color information. Use of two estimates provides a measure of uncertainty in the fluxes. Along with inventories of other emissions, these data-derived fluxes are used in transport models to assess their consistency with atmospheric CO2 observations. Closure is achieved by using a four-dimensional data assimilation (inverse) approach that adjusts the terrestrial biosphere fluxes to make them consistent with the atmospheric CO2 observations. Results will be shown, illustrating the year-to-year variations in land biospheric and oceanic fluxes computed in the FPP. The signals of these surface-flux variations on atmospheric CO2 will be isolated using forward modeling tools, which also incorporate estimates of transport error. The results will be discussed in the context of interannual variability of observed atmospheric CO2 distributions.

Pawson, S.↗

Operational Use of the Air Quality Monitor on ISS and Potential for Air Quality Monitoring Onboard Submarines

The air quality monitor (AQM) began operations on the International Space Station (ISS) in March 2013 and was validated for operational use in January 2014. The AQM is a gas chromatograph-differential mobility spectrometer that currently monitors 22 target compounds in the ISS atmosphere. Data are collected twice per week, although data collection can be more frequent in contingency situations. In its second year, the AQM has provided data to decision-makers on several ISS contaminant related issues in both air and water. AQM has been used in strictly air incidents, such as a potential ammonia leak, and to investigate air contaminants affecting the water processing (excess ethanol). In the latter case data from water monitors and AQM were compared to understand the issue with the water processor. Additionally, the AQM has been moved to different ISS modules to determine whether air is sufficiently mixed between modules so that a central LAB module location is representative of the entire ISS atmosphere. Historic data on the ISS atmosphere in different modules from archival samples (ground lab analysis) suggest that the atmosphere is usually homogenous. This presentation will briefly describe the technical aspects of the AQM operations and summarize the validation results. The main focus of the presentation will be to discuss the results from the AQM survey of the ISS modules and to show how the AQM data has contributed to an understanding of environmental issues that have arisen on ISS. Presentation of a potential ammonia leak (indicated by an alarm) in 2015 will illustrate the use and value of the AQM in such situations.

Limero, Thomas↗